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What field is the article from? | Title: Efficient Large Language Models Fine-Tuning On Graphs
Abstract: Learning from Text-Attributed Graphs (TAGs) has attracted significant
attention due to its wide range of real-world applications. The rapid evolution
of large language models (LLMs) has revolutionized the way we process textual
data, which indicates... | Machine Learning |
What field is the article from? | Title: MRxaI: Black-Box Explainability for Image Classifiers in a Medical Setting
Abstract: Existing tools for explaining the output of image classifiers can be divided
into white-box, which rely on access to the model internals, and black-box,
agnostic to the model. As the usage of AI in the medical domain grows, so t... | Computer Vision |
What field is the article from? | Title: SparseSpikformer: A Co-Design Framework for Token and Weight Pruning in Spiking Transformer
Abstract: As the third-generation neural network, the Spiking Neural Network (SNN) has
the advantages of low power consumption and high energy efficiency, making it
suitable for implementation on edge devices. More recent... | Computer Vision |
What field is the article from? | Title: ResMGCN: Residual Message Graph Convolution Network for Fast Biomedical Interactions Discovering
Abstract: Biomedical information graphs are crucial for interaction discovering of
biomedical information in modern age, such as identification of multifarious
molecular interactions and drug discovery, which attract... | Machine Learning |
What field is the article from? | Title: Enhancing Object Coherence in Layout-to-Image Synthesis
Abstract: Layout-to-image synthesis is an emerging technique in conditional image
generation. It aims to generate complex scenes, where users require fine
control over the layout of the objects in a scene. However, it remains
challenging to control the obje... | Computer Vision |
What field is the article from? | Title: Breaking the Token Barrier: Chunking and Convolution for Efficient Long Text Classification with BERT
Abstract: Transformer-based models, specifically BERT, have propelled research in
various NLP tasks. However, these models are limited to a maximum token limit
of 512 tokens. Consequently, this makes it non-triv... | Computational Linguistics |
What field is the article from? | Title: Data Center Audio/Video Intelligence on Device (DAVID) -- An Edge-AI Platform for Smart-Toys
Abstract: An overview is given of the DAVID Smart-Toy platform, one of the first Edge
AI platform designs to incorporate advanced low-power data processing by neural
inference models co-located with the relevant image or... | Artificial Intelligence |
What field is the article from? | Title: Adaptive parameter sharing for multi-agent reinforcement learning
Abstract: Parameter sharing, as an important technique in multi-agent systems, can
effectively solve the scalability issue in large-scale agent problems. However,
the effectiveness of parameter sharing largely depends on the environment
setting. W... | Artificial Intelligence |
What field is the article from? | Title: TaBIIC: Taxonomy Building through Iterative and Interactive Clustering
Abstract: Building taxonomies is often a significant part of building an ontology, and
many attempts have been made to automate the creation of such taxonomies from
relevant data. The idea in such approaches is either that relevant definition... | Artificial Intelligence |
What field is the article from? | Title: No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation
Abstract: Ensuring fairness in Recommendation Systems (RSs) across demographic groups
is critical due to the increased integration of RSs in applications such as
personalized healthcare, finance, and e-commerce. Graph-based RSs pl... | Information Retrieval |
What field is the article from? | Title: Adapting Fake News Detection to the Era of Large Language Models
Abstract: In the age of large language models (LLMs) and the widespread adoption of
AI-driven content creation, the landscape of information dissemination has
witnessed a paradigm shift. With the proliferation of both human-written and
machine-gene... | Computational Linguistics |
What field is the article from? | Title: FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
Abstract: Multivariate time series (MTS) forecasting has shown great importance in
numerous industries. Current state-of-the-art graph neural network (GNN)-based
forecasting methods usually require both graph networks (e.g.... | Machine Learning |
What field is the article from? | Title: Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
Abstract: We propose a conceptually simple and lightweight framework for improving the
robustness of vision models through the combination of knowledge distillation
and data augmentation. We address the conjecture that larger models... | Machine Learning |
What field is the article from? | Title: DiffiT: Diffusion Vision Transformers for Image Generation
Abstract: Diffusion models with their powerful expressivity and high sample quality
have enabled many new applications and use-cases in various domains. For sample
generation, these models rely on a denoising neural network that generates
images by itera... | Computer Vision |
What field is the article from? | Title: VIM: Probing Multimodal Large Language Models for Visual Embedded Instruction Following
Abstract: We introduce VISUAL EMBEDDED INSTRUCTION (VIM), a new framework designed to
evaluate the visual instruction following capability of Multimodal Large
Language Models (MLLMs). As illustrated in Figure 2, VIM challenge... | Computer Vision |
What field is the article from? | Title: Ovarian Cancer Data Analysis using Deep Learning: A Systematic Review from the Perspectives of Key Features of Data Analysis and AI Assurance
Abstract: Background and objectives: By extracting this information, Machine or Deep
Learning (ML/DL)-based autonomous data analysis tools can assist clinicians and
cancer... | Machine Learning |
What field is the article from? | Title: Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs
Abstract: Recent work in Natural Language Processing and Computer Vision has been using
textual information -- e.g., entity names and descriptions -- available in
knowledge graphs to ground neural models to high-quality str... | Artificial Intelligence |
What field is the article from? | Title: Robust Representation Learning for Unified Online Top-K Recommendation
Abstract: In large-scale industrial e-commerce, the efficiency of an online
recommendation system is crucial in delivering highly relevant item/content
advertising that caters to diverse business scenarios. However, most existing
studies focu... | Information Retrieval |
What field is the article from? | Title: N-Critics: Self-Refinement of Large Language Models with Ensemble of Critics
Abstract: We propose a self-correction mechanism for Large Language Models (LLMs) to
mitigate issues such as toxicity and fact hallucination. This method involves
refining model outputs through an ensemble of critics and the model's own... | Computational Linguistics |
What field is the article from? | Title: SoftMAC: Differentiable Soft Body Simulation with Forecast-based Contact Model and Two-way Coupling with Articulated Rigid Bodies and Clothes
Abstract: Differentiable physics simulation provides an avenue for tackling previously
intractable challenges through gradient-based optimization, thereby greatly
improvin... | Robotics |
What field is the article from? | Title: Synaptic Sampling of Neural Networks
Abstract: Probabilistic artificial neural networks offer intriguing prospects for
enabling the uncertainty of artificial intelligence methods to be described
explicitly in their function; however, the development of techniques that
quantify uncertainty by well-understood meth... | Artificial Intelligence |
What field is the article from? | Title: QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation
Abstract: Federated Unlearning (FU) aims to delete specific training data from an ML
model trained using Federated Learning (FL). We introduce QuickDrop, an
efficient and original FU method that utilizes dataset distillation (DD) to
acc... | Machine Learning |
What field is the article from? | Title: Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? -- Application to proton therapy dose prediction for head and neck cancer patients
Abstract: Estimating the uncertainty of deep learning models in a reliable and
efficient way has remained an open problem, where many d... | Machine Learning |
What field is the article from? | Title: DMLR: Data-centric Machine Learning Research -- Past, Present and Future
Abstract: Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and
meetings prior, in this report we outline the relevance of community engagement
and infrastructure development for the creation of next-generation public
dat... | Machine Learning |
What field is the article from? | Title: Prompt Tuning for Zero-shot Compositional Learning
Abstract: Open World Compositional Zero-Shot Learning (OW-CZSL) is known to be an
extremely challenging task, which aims to recognize unseen compositions formed
from seen attributes and objects without any prior assumption of the output
space. In order to achiev... | Computer Vision |
What field is the article from? | Title: Ask One More Time: Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios
Abstract: Although chain-of-thought (CoT) prompting combined with language models has
achieved encouraging results on complex reasoning tasks, the naive greedy
decoding used in CoT prompting usually causes the repet... | Computational Linguistics |
What field is the article from? | Title: Long Story Short: a Summarize-then-Search Method for Long Video Question Answering
Abstract: Large language models such as GPT-3 have demonstrated an impressive
capability to adapt to new tasks without requiring task-specific training data.
This capability has been particularly effective in settings such as narr... | Computer Vision |
What field is the article from? | Title: New Approach for an Affective Computing-Driven Quality of Experience (QoE) Prediction
Abstract: In human interactions, emotion recognition is crucial. For this reason, the
topic of computer-vision approaches for automatic emotion recognition is
currently being extensively researched. Processing multi-channel
ele... | Computer Vision |
What field is the article from? | Title: Hashing it Out: Predicting Unhealthy Conversations on Twitter
Abstract: Personal attacks in the context of social media conversations often lead to
fast-paced derailment, leading to even more harmful exchanges being made.
State-of-the-art systems for the detection of such conversational derailment
often make use... | Computational Linguistics |
What field is the article from? | Title: A Simple yet Efficient Ensemble Approach for AI-generated Text Detection
Abstract: Recent Large Language Models (LLMs) have demonstrated remarkable capabilities
in generating text that closely resembles human writing across wide range of
styles and genres. However, such capabilities are prone to potential abuse,... | Computational Linguistics |
What field is the article from? | Title: CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction
Abstract: Existing works on Aspect Sentiment Triplet Extraction (ASTE) explicitly focus
on developing more efficient fine-tuning techniques for the task. Instead, our
motivation is to come up with a g... | Computational Linguistics |
What field is the article from? | Title: LLMEval: A Preliminary Study on How to Evaluate Large Language Models
Abstract: Recently, the evaluation of Large Language Models has emerged as a popular
area of research. The three crucial questions for LLM evaluation are ``what,
where, and how to evaluate''. However, the existing research mainly focuses on
th... | Artificial Intelligence |
What field is the article from? | Title: Detecting value-expressive text posts in Russian social media
Abstract: Basic values are concepts or beliefs which pertain to desirable end-states
and transcend specific situations. Studying personal values in social media can
illuminate how and why societal values evolve especially when the stimuli-based
method... | Computational Linguistics |
What field is the article from? | Title: Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents
Abstract: Deep reinforcement learning (RL) has achieved remarkable success in solving
complex tasks through its integration with deep neural networks (DNNs) as
function approximators. However, the reliance on DNNs has introduced... | Machine Learning |
What field is the article from? | Title: PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering
Abstract: Information-seeking questions in long-form question answering (LFQA) often
prove misleading due to ambiguity or false presupposition in the question.
While many existing approaches handle misleading questions, they a... | Computational Linguistics |
What field is the article from? | Title: Inclusive Portraits: Race-Aware Human-in-the-Loop Technology
Abstract: AI has revolutionized the processing of various services, including the
automatic facial verification of people. Automated approaches have demonstrated
their speed and efficiency in verifying a large volume of faces, but they can
face challen... | Human-Computer Interaction |
What field is the article from? | Title: Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework
Abstract: With the increasing integration of frontier large language models (LLMs) into
society and the economy, decisions related to their training, deployment, and
use have far-reaching implications. ... | Computers and Society |
What field is the article from? | Title: Inspecting Model Fairness in Ultrasound Segmentation Tasks
Abstract: With the rapid expansion of machine learning and deep learning (DL),
researchers are increasingly employing learning-based algorithms to alleviate
diagnostic challenges across diverse medical tasks and applications. While
advancements in diagno... | Computer Vision |
What field is the article from? | Title: Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature
Abstract: The quickly-expanding nature of published medical literature makes it
challenging for clinicians and researchers to keep up with and summarize
recent, relevant findings ... | Information Retrieval |
What field is the article from? | Title: EipFormer: Emphasizing Instance Positions in 3D Instance Segmentation
Abstract: 3D instance segmentation plays a crucial role in comprehending 3D scenes.
Despite recent advancements in this field, existing approaches exhibit certain
limitations. These methods often rely on fixed instance positions obtained from
... | Computer Vision |
What field is the article from? | Title: Anomalous Behavior Detection in Trajectory Data of Older Drivers
Abstract: Given a road network and a set of trajectory data, the anomalous behavior
detection (ABD) problem is to identify drivers that show significant
directional deviations, hardbrakings, and accelerations in their trips. The ABD
problem is impo... | Artificial Intelligence |
What field is the article from? | Title: Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit
Abstract: Transformer requires a fixed number of layers and heads which makes them
inflexible to the complexity of individual samples and expensive in training
and inference. To address this, we propose a sample-b... | Machine Learning |
What field is the article from? | Title: Improving Traffic Density Forecasting in Intelligent Transportation Systems Using Gated Graph Neural Networks
Abstract: This study delves into the application of graph neural networks in the realm
of traffic forecasting, a crucial facet of intelligent transportation systems.
Accurate traffic predictions are vita... | Machine Learning |
What field is the article from? | Title: HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models
Abstract: This paper explores advancements in high-fidelity personalized image
generation through the utilization of pre-trained text-to-image diffusion
models. While previous approaches have made significant strides in generating
versatil... | Computer Vision |
What field is the article from? | Title: CPST: Comprehension-Preserving Style Transfer for Multi-Modal Narratives
Abstract: We investigate the challenges of style transfer in multi-modal visual
narratives. Among static visual narratives such as comics and manga, there are
distinct visual styles in terms of presentation. They include style features
acro... | Computer Vision |
What field is the article from? | Title: When Graph Data Meets Multimodal: A New Paradigm for Graph Understanding and Reasoning
Abstract: Graph data is ubiquitous in the physical world, and it has always been a
challenge to efficiently model graph structures using a unified paradigm for
the understanding and reasoning on various graphs. Moreover, in th... | Artificial Intelligence |
What field is the article from? | Title: Fine-tuning pre-trained extractive QA models for clinical document parsing
Abstract: Electronic health records (EHRs) contain a vast amount of high-dimensional
multi-modal data that can accurately represent a patient's medical history.
Unfortunately, most of this data is either unstructured or semi-structured,
r... | Computational Linguistics |
What field is the article from? | Title: Deep Image Semantic Communication Model for Artificial Intelligent Internet of Things
Abstract: With the rapid development of Artificial Intelligent Internet of Things
(AIoT), the image data from AIoT devices has been witnessing the explosive
increasing. In this paper, a novel deep image semantic communication m... | Computer Vision |
What field is the article from? | Title: Prompt Sketching for Large Language Models
Abstract: Many recent prompting strategies for large language models (LLMs) query the
model multiple times sequentially -- first to produce intermediate results and
then the final answer. However, using these methods, both decoder and model are
unaware of potential foll... | Computational Linguistics |
What field is the article from? | Title: Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation
Abstract: Two-tower models are a prevalent matching framework for recommendation, which
have been widely deployed in industrial applications. The success of two-tower
matching attributes to its efficiency in retrieval am... | Information Retrieval |
What field is the article from? | Title: Simple Transferability Estimation for Regression Tasks
Abstract: We consider transferability estimation, the problem of estimating how well
deep learning models transfer from a source to a target task. We focus on
regression tasks, which received little previous attention, and propose two
simple and computationa... | Machine Learning |
What field is the article from? | Title: Equivariant Flow Matching with Hybrid Probability Transport
Abstract: The generation of 3D molecules requires simultaneously deciding the
categorical features~(atom types) and continuous features~(atom coordinates).
Deep generative models, especially Diffusion Models (DMs), have demonstrated
effectiveness in gen... | Machine Learning |
What field is the article from? | Title: Competition-Level Problems are Effective LLM Evaluators
Abstract: Large language models (LLMs) have demonstrated impressive reasoning
capabilities, yet there is ongoing debate about these abilities and the
potential data contamination problem recently. This paper aims to evaluate the
reasoning capacities of LLMs... | Computational Linguistics |
What field is the article from? | Title: Parameter Exchange for Robust Dynamic Domain Generalization
Abstract: Agnostic domain shift is the main reason of model degradation on the unknown
target domains, which brings an urgent need to develop Domain Generalization
(DG). Recent advances at DG use dynamic networks to achieve training-free
adaptation on t... | Computer Vision |
What field is the article from? | Title: Understanding and Leveraging the Learning Phases of Neural Networks
Abstract: The learning dynamics of deep neural networks are not well understood. The
information bottleneck (IB) theory proclaimed separate fitting and compression
phases. But they have since been heavily debated. We comprehensively analyze
the ... | Machine Learning |
What field is the article from? | Title: Know Your Audience: Do LLMs Adapt to Different Age and Education Levels?
Abstract: Large language models (LLMs) offer a range of new possibilities, including
adapting the text to different audiences and their reading needs. But how well
do they adapt? We evaluate the readability of answers generated by four
stat... | Computational Linguistics |
What field is the article from? | Title: Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal
Abstract: In imitation learning for planning, parameters of heuristic functions are
optimized against a set of solved problem instances. This work revisits the
necessary and sufficient conditions of strictly optimally efficient heuristics
for for... | Artificial Intelligence |
What field is the article from? | Title: Mirror: A Universal Framework for Various Information Extraction Tasks
Abstract: Sharing knowledge between information extraction tasks has always been a
challenge due to the diverse data formats and task variations. Meanwhile, this
divergence leads to information waste and increases difficulties in building
com... | Computational Linguistics |
What field is the article from? | Title: Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions
Abstract: Recent advances in Large Language Models (LLMs) have presented new
opportunities for integrating Artificial General Intelligence (AGI) into
biological research and education. This study evaluated the capabilities o... | Computational Linguistics |
What field is the article from? | Title: WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models
Abstract: We propose WorldSense, a benchmark designed to assess the extent to which
LLMs are consistently able to sustain tacit world models, by testing how they
draw simple inferences from descriptions of simple arrangements of en... | Computational Linguistics |
What field is the article from? | Title: Translating Universal Scene Descriptions into Knowledge Graphs for Robotic Environment
Abstract: Robots performing human-scale manipulation tasks require an extensive amount
of knowledge about their surroundings in order to perform their actions
competently and human-like. In this work, we investigate the use of... | Robotics |
What field is the article from? | Title: Neurosymbolic Value-Inspired AI (Why, What, and How)
Abstract: The rapid progression of Artificial Intelligence (AI) systems, facilitated by
the advent of Large Language Models (LLMs), has resulted in their widespread
application to provide human assistance across diverse industries. This trend
has sparked signi... | Artificial Intelligence |
What field is the article from? | Title: Are "Hierarchical" Visual Representations Hierarchical?
Abstract: Learned visual representations often capture large amounts of semantic
information for accurate downstream applications. Human understanding of the
world is fundamentally grounded in hierarchy. To mimic this and further improve
representation capa... | Computer Vision |
What field is the article from? | Title: Building a Safer Maritime Environment Through Multi-Path Long-Term Vessel Trajectory Forecasting
Abstract: Maritime transportation is paramount in achieving global economic growth,
entailing concurrent ecological obligations in sustainability and safeguarding
endangered marine species, most notably preserving la... | Machine Learning |
What field is the article from? | Title: An Open Source Data Contamination Report for Large Language Models
Abstract: Data contamination in language model evaluation is increasingly prevalent as
the popularity of large language models. It allows models to "cheat" via
memorisation instead of displaying true capabilities. Therefore, contamination
analysi... | Computational Linguistics |
What field is the article from? | Title: Pixel-Superpixel Contrastive Learning and Pseudo-Label Correction for Hyperspectral Image Clustering
Abstract: Hyperspectral image (HSI) clustering is gaining considerable attention owing
to recent methods that overcome the inefficiency and misleading results from
the absence of supervised information. Contrasti... | Computer Vision |
What field is the article from? | Title: The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
Abstract: As Federated Learning (FL) grows in popularity, new decentralized frameworks
are becoming widespread. These frameworks leverage the benefits of
decentralized environments to enable fast and energy-efficient inter-devi... | Cryptography and Security |
What field is the article from? | Title: In-Context Learning Functions with Varying Number of Minima
Abstract: Large Language Models (LLMs) have proven effective at In-Context Learning
(ICL), an ability that allows them to create predictors from labeled examples.
Few studies have explored the interplay between ICL and specific properties of
functions i... | Machine Learning |
What field is the article from? | Title: Symbol-LLM: Towards Foundational Symbol-centric Interface For Large Language Models
Abstract: Large Language Models (LLMs) have greatly propelled the progress in natural
language(NL)-centric tasks based on NL interface. However, the NL form is not
enough for world knowledge. Current works focus on this question ... | Computational Linguistics |
What field is the article from? | Title: Graph Deep Learning for Time Series Forecasting
Abstract: Graph-based deep learning methods have become popular tools to process
collections of correlated time series. Differently from traditional
multivariate forecasting methods, neural graph-based predictors take advantage
of pairwise relationships by conditio... | Machine Learning |
What field is the article from? | Title: A Multilingual Virtual Guide for Self-Attachment Technique
Abstract: In this work, we propose a computational framework that leverages existing
out-of-language data to create a conversational agent for the delivery of
Self-Attachment Technique (SAT) in Mandarin. Our framework does not require
large-scale human t... | Computational Linguistics |
What field is the article from? | Title: NeuroWrite: Predictive Handwritten Digit Classification using Deep Neural Networks
Abstract: The rapid evolution of deep neural networks has revolutionized the field of
machine learning, enabling remarkable advancements in various domains. In this
article, we introduce NeuroWrite, a unique method for predicting ... | Computer Vision |
What field is the article from? | Title: Investigating Relative Performance of Transfer and Meta Learning
Abstract: Over the past decade, the field of machine learning has experienced
remarkable advancements. While image recognition systems have achieved
impressive levels of accuracy, they continue to rely on extensive training
datasets. Additionally, ... | Machine Learning |
What field is the article from? | Title: Diffusion Cocktail: Fused Generation from Diffusion Models
Abstract: Diffusion models excel at generating high-quality images and are easy to
extend, making them extremely popular among active users who have created an
extensive collection of diffusion models with various styles by fine-tuning
base models such a... | Computer Vision |
What field is the article from? | Title: Utilizing Speech Emotion Recognition and Recommender Systems for Negative Emotion Handling in Therapy Chatbots
Abstract: Emotional well-being significantly influences mental health and overall
quality of life. As therapy chatbots become increasingly prevalent, their
ability to comprehend and respond empathetical... | Computational Linguistics |
What field is the article from? | Title: Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge
Abstract: Uplift modeling is a fundamental component of marketing effect modeling,
which is commonly employed to evaluate the effects of treatments on outcomes.
Through uplift modeling, we can identify the treatment with the greatest
be... | Machine Learning |
What field is the article from? | Title: Flexible Model Interpretability through Natural Language Model Editing
Abstract: Model interpretability and model editing are crucial goals in the age of
large language models. Interestingly, there exists a link between these two
goals: if a method is able to systematically edit model behavior with regard to
a h... | Computational Linguistics |
What field is the article from? | Title: Eliciting Latent Knowledge from Quirky Language Models
Abstract: Eliciting Latent Knowledge (ELK) aims to find patterns in a neural network's
activations which robustly track the true state of the world, even when the
network's overt output is false or misleading. To further ELK research, we
introduce a suite of... | Machine Learning |
What field is the article from? | Title: Magicoder: Source Code Is All You Need
Abstract: We introduce Magicoder, a series of fully open-source (code, weights, and
data) Large Language Models (LLMs) for code that significantly closes the gap
with top code models while having no more than 7B parameters. Magicoder models
are trained on 75K synthetic inst... | Computational Linguistics |
What field is the article from? | Title: Low-power, Continuous Remote Behavioral Localization with Event Cameras
Abstract: Researchers in natural science need reliable methods for quantifying animal
behavior. Recently, numerous computer vision methods emerged to automate the
process. However, observing wild species at remote locations remains a
challen... | Computer Vision |
What field is the article from? | Title: Efficiently Quantifying Individual Agent Importance in Cooperative MARL
Abstract: Measuring the contribution of individual agents is challenging in cooperative
multi-agent reinforcement learning (MARL). In cooperative MARL, team
performance is typically inferred from a single shared global reward. Arguably,
amon... | Artificial Intelligence |
What field is the article from? | Title: Scalable Decentralized Cooperative Platoon using Multi-Agent Deep Reinforcement Learning
Abstract: Cooperative autonomous driving plays a pivotal role in improving road
capacity and safety within intelligent transportation systems, particularly
through the deployment of autonomous vehicles on urban streets. By e... | Robotics |
What field is the article from? | Title: Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation
Abstract: POI recommendation is practically important to facilitate various
Location-Based Social Network services, and has attracted rising research
attention recently. Existing works generally assume the available POI check-ins
reported... | Information Retrieval |
What field is the article from? | Title: MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems using a Dual Variational Generative Adversarial Network
Abstract: Deep generative models are promising in detecting novel cyber-physical
attacks, mitigating the vulnerability of Cyber-physical systems (CPSs) without
relying on labeled information. Nonetheles... | Cryptography and Security |
What field is the article from? | Title: MMDesign: Multi-Modality Transfer Learning for Generative Protein Design
Abstract: Protein design involves generating protein sequences based on their
corresponding protein backbones. While deep generative models show promise for
learning protein design directly from data, the lack of publicly available
structur... | Artificial Intelligence |
What field is the article from? | Title: Evaluating the Efficacy of Hybrid Deep Learning Models in Distinguishing AI-Generated Text
Abstract: My research investigates the use of cutting-edge hybrid deep learning models
to accurately differentiate between AI-generated text and human writing. I
applied a robust methodology, utilising a carefully selected... | Computational Linguistics |
What field is the article from? | Title: Leveraging AI-derived Data for Carbon Accounting: Information Extraction from Alternative Sources
Abstract: Carbon accounting is a fundamental building block in our global path to
emissions reduction and decarbonization, yet many challenges exist in achieving
reliable and trusted carbon accounting measures. We m... | Computational Linguistics |
What field is the article from? | Title: Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization
Abstract: Many real-world decision processes are modeled by optimization problems whose
defining parameters are unknown and must be inferred from observable data. The
Predict-Then-Optimize framework uses machine learning models ... | Machine Learning |
What field is the article from? | Title: Filtered Semi-Markov CRF
Abstract: Semi-Markov CRF has been proposed as an alternative to the traditional Linear
Chain CRF for text segmentation tasks such as Named Entity Recognition (NER).
Unlike CRF, which treats text segmentation as token-level prediction, Semi-CRF
considers segments as the basic unit, makin... | Computational Linguistics |
What field is the article from? | Title: On the Difficulty of Defending Contrastive Learning against Backdoor Attacks
Abstract: Recent studies have shown that contrastive learning, like supervised
learning, is highly vulnerable to backdoor attacks wherein malicious functions
are injected into target models, only to be activated by specific triggers.
Ho... | Cryptography and Security |
What field is the article from? | Title: The Analysis and Extraction of Structure from Organizational Charts
Abstract: Organizational charts, also known as org charts, are critical representations
of an organization's structure and the hierarchical relationships between its
components and positions. However, manually extracting information from org
cha... | Computer Vision |
What field is the article from? | Title: Contact Energy Based Hindsight Experience Prioritization
Abstract: Multi-goal robot manipulation tasks with sparse rewards are difficult for
reinforcement learning (RL) algorithms due to the inefficiency in collecting
successful experiences. Recent algorithms such as Hindsight Experience Replay
(HER) expedite le... | Robotics |
What field is the article from? | Title: Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review
Abstract: With the rapid development of artificial intelligence, large language models
(LLMs) have shown promising capabilities in mimicking human-level language
comprehension and reasoning. This has sparked signi... | Computational Linguistics |
What field is the article from? | Title: Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents
Abstract: Data heterogeneity presents significant challenges for federated learning
(FL). Recently, dataset distillation techniques have been introduced, and
performed at the client level, to attempt t... | Machine Learning |
What field is the article from? | Title: Identification of Knowledge Neurons in Protein Language Models
Abstract: Neural language models have become powerful tools for learning complex
representations of entities in natural language processing tasks. However,
their interpretability remains a significant challenge, particularly in domains
like computati... | Machine Learning |
What field is the article from? | Title: Advances in ACL2 Proof Debugging Tools
Abstract: The experience of an ACL2 user generally includes many failed proof attempts.
A key to successful use of the ACL2 prover is the effective use of tools to
debug those failures. We focus on changes made after ACL2 Version 8.5: the
improved break-rewrite utility and ... | Artificial Intelligence |
What field is the article from? | Title: Supported Trust Region Optimization for Offline Reinforcement Learning
Abstract: Offline reinforcement learning suffers from the out-of-distribution issue and
extrapolation error. Most policy constraint methods regularize the density of
the trained policy towards the behavior policy, which is too restrictive in
... | Machine Learning |
What field is the article from? | Title: Integrating Language Models into Direct Speech Translation: An Inference-Time Solution to Control Gender Inflection
Abstract: When translating words referring to the speaker, speech translation (ST)
systems should not resort to default masculine generics nor rely on potentially
misleading vocal traits. Rather, t... | Computational Linguistics |
What field is the article from? | Title: AI-based Wildfire Prevention, Detection and Suppression System
Abstract: Wildfires pose a serious threat to the environment of the world. The global
wildfire season length has increased by 19% and severe wildfires have besieged
nations around the world. Every year, forests are burned by wildfires, causing
vast a... | Artificial Intelligence |
What field is the article from? | Title: Assessing AI Chatbots Performance in Comprehensive Standardized Test Preparation; A Case Study with GRE
Abstract: This research paper presents a comprehensive evaluation of the performance of
three artificial 10 intelligence chatbots: Bing, ChatGPT, and GPT-4, in
addressing standardized test questions. Graduate ... | Computational Linguistics |
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